Data and AI Governance

Course overview

This professional programme equips participants with the frameworks, methods and practical tools needed to establish and improve data and artificial intelligence governance across an organisation. It connects data management, responsible AI, risk controls, privacy, security, accountability and business value.

Through instructor-led sessions, applied exercises and organisational case studies, learners explore how to define governance roles, establish policies and controls, assess AI use cases, improve data quality, document decisions and monitor governance performance throughout the data and AI lifecycle.

Course details

Duration: 90 hours

Delivery: Virtual instructor-led training

Learning approach: Live teaching, guided discussions, practical exercises and case studies

Core learning areas

• Data governance operating models, ownership, stewardship and accountability
• Data management principles, data quality, metadata and lifecycle controls
• Data privacy, protection, security and responsible data use
• AI governance principles, responsible AI and human oversight
• AI risk assessment, model lifecycle controls, transparency and explainability
• Governance policies, standards, regulatory alignment and audit evidence
• Third-party AI, data sharing, procurement and supplier risk
• Governance metrics, monitoring, incident handling and continuous improvement
• Practical development of a data and AI governance roadmap

Expected course outcomes

By the end of the programme, participants should be able to:

• Develop a fit-for-purpose data and AI governance framework for an organisation.
• Define governance roles, decision rights, accountability and escalation paths.
• Apply data quality, privacy, security and lifecycle controls to business use cases.
• Identify and assess risks associated with AI systems and their supporting data.
• Recommend proportionate controls for responsible, transparent and human-supervised AI.
• Map governance practices to relevant organisational policies and applicable standards or regulations.
• Document governance decisions, maintain evidence and support audit readiness.
• Define measurable governance indicators and prepare an actionable implementation roadmap.

Course fees

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Payment details

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